So Much for the Turing Test … and for Consequentialism

In a few sentences, and with his characteristic penetrating trenchance, Chastek demolishes the Turing Test, and for that matter all arguments from similarity of causal effects; I post here without apology his entire argument, on account of its brevity, precision, and devastation:

One principle of (strong/sci-fi) AI seems to be that what can replicate the effects of intelligence is intelligence, e.g. the Turing test, or the present claim by some philosophers that a Chinese room would be intelligence.

So imagine you rig up a track and trolley to accelerate at 9.8 m/s2. This perfectly replicates the effects of falling, and so is artificial falling. It deserves the name too: you could strap a helmet to the front of your train and drive at a wall 10 feet away, and it will tell you what the helmet would look like if dropped from 10 feet. But for all that the helmet at the front of your train is obviously being pushed and not falling – falling is something bodies do by themselves and being pushed isn’t. The difference is relevant to AI, for just as falling is to being pushed so thinking for oneself is to being a tool, instrument or machine. Both latter are acted on by others, and have the form by which they act in a transient way and not as a principal agent.

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Mystery and Order; the right and left hemispheres

Mystery and Order; the right and left hemispheres

In The Master and His Emissary, Iain McGilchrist writes that a creature like a bird needs two types of consciousness simultaneously. It needs to be able to focus on something specific, such as pecking at food, while it also needs to keep an eye out for predators which requires a more general awareness of environment.

These are quite different activities. The Left Hemisphere (LH) is adapted for a narrow focus. The Right Hemisphere (RH) for the broad. The brains of human beings have the same division of function.

The LH governs the right side of the body, the RH, the left side. With birds, the left eye (RH) looks for predators, the right eye (LH) focuses on food and specifics. Since danger can take many forms and is unpredictable, the RH has to be very open-minded. Continue reading

The Halting Problem – there is, definitively, more to thinking than computation

Alan Turing

Alan Turing

Kurt Gödel’s Incompleteness Theorem[1] was inspired by David Hilbert’s question “Are the axioms of a formal system sufficient to derive every statement that is true in all models of the system?” Hilbert played the same role regarding Alan Turing’s proof of the halting problem. Hilbert had asked: “Is there some mechanical procedure [an algorithm] for answering all mathematical problems, belonging to some broad, but well-defined class?”[2] In German this is called Entscheidungsproblem – the decision problem.[3]

Turing found that he could answer this question by framing it in terms of a Turing machine[4] – could there be a program that could determine whether any other arbitrary computer program and input would eventually stop or just loop forever? This was called the halting problem.

“Alan Turing proved in 1936 that a general algorithm to solve the halting problem for all possible program-input pairs cannot exist.”[5]

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